AI stocks lost $1.45 trillion of market value in one session on 5 November, Nvidia fell 9.26% and, by the close in Asia the next day, ten AI companies in Seoul, Tokyo and Taipei were about $261 billion lower. These are the twelve numbers from our coverage of the selloff, each taken from a piece we have already published, with Nasdaq and Asian exchange prices from the official closes.
Business Pill · Financial Conditions
An evergreen Business Engineer explainer on how financial conditions shape what companies can raise. It teaches the general idea only and does not discuss these markets.
The key insight: In one session, 12 AI stocks lost $1,447.4 billion and Nvidia fell 9.26%; by Asia’s close the next day, ten Asian AI companies were about $261 billion lower and the Nikkei closed 20.6% below its record.
About $261 billion. What ten Asian AI companies in Seoul, Tokyo and Taipei lost at the 6 November close: about $126 billion, $38.1 billion and $97.0 billion, converted at different times’ exchange rates, so a rough sum (our arithmetic). Source: TSMC Opened Limit-Down; Taiwan AI Stocks Lost $97B at Close.
$1 trillion. Where one investor said Anthropic’s IPO valuation could end up, against the $1.5 trillion expected, according to Techmeme’s summary of a Wall Street Journal report; one investor planning to buy into the IPO later told the Journal the raise could be around $80 billion, against the up to $100 billion the Journal had reported. Sources: One Anthropic IPO Investor Floats $1T, 14.7x Its Q3 Pace and Anthropic Run Rate Tops $80B as IPO Raise May Shrink to $80B.
Market value lost by four overlapping groups on 5 and 6 November 2026, in $ billions. The groups overlap and must not be added. Data: Nasdaq, KRX, TSE and TWSE official closes; Bloomberg Billionaires Index. Our arithmetic, from our own coverage.
The four dollar losses in the chart measure different groups and must not be added: Nvidia is in both the 12-stock basket and the wealth of its chief executive, and SpaceX and Tesla are counted over two sessions, not one. The ten Asian companies are converted at exchange rates read at different times on 6 November.
Stocks, credit and private valuations moved on the same days: SpaceX’s default swaps reached a peak, CoreWeave’s 2032 notes traded at 76.42 cents, and one investor floated a $1 trillion valuation for Anthropic’s IPO, according to Techmeme’s summary of a Wall Street Journal report.
The framework says: “It is a sovereign-scale financing problem dressed in tech-company clothing โ and the financial architecture is starting to invert.”
As we read it, these two days priced that financing problem in stocks, swaps and notes at once. The framework itself does not discuss these markets.
What Is Not Established
This piece adds no new reporting: every figure comes from our earlier pieces, which credit their own sources (Nasdaq, Cboe, KRX, TSE and TWSE closes, FINRA TRACE, Markit via Walter Bloomberg, the Bloomberg Billionaires Index, and The Wall Street Journal via Techmeme). It does not explain why the stocks fell or forecast what they will do next, and the dollar figures are not additive.
This Week In The AI Supercycle
Anthropic’s Reality Check, The Capital Squeeze, & The New World Order
This week’s issue: for two years the AI build-out was priced as a growthstory. This week it started being priced as a credit story.
Over two sessions the selloff showed up in AI stocks ($1.45 trillion off 12 names), in Asia (about $261 billion off ten companies), in credit (SpaceX swaps at a peak) and in the Anthropic IPO talks ($1 trillion floated against $1.5 trillion).
A note on sourcing. This is a recap: every figure is taken from an earlier FourWeekMBA piece linked in the list, using the corrected official closing prices, and those pieces credit their own sources. Rankings, sums and conversions are our arithmetic; the dollar figures in the chart overlap and are not additive.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
